Next week I will be heading to the DataWorks Summit in San Jose (formerly Hadoop Summit). The DataWorks summit is one of the top conferences for the Hadoop Ecosystem. Last year was first DataWorks Summit I’ve missed the past 3 years, but this year I’m back. I’m happy to announce this year I have a breakout sessions.

My session will focus on the Future Architectures of Streaming Analytics. I will cover how these architectures will support the future of Streaming Analytics. In the past few years the Hadoop community has focused on the processing of data from streaming data sources with Storm, Spark, Flink, Beam and other projects. Now as we enter in era of massive streams of data it’s time to focus on how we store and scale theses systems. Gartner predicts that by 2020 we will reach 20.4 billion connected devices. Now more than ever we are going to need systems with auto-scaling and unlimited retention. Projects like Pravega emerging to abstract away the storage layer in massive data analytics architectures. Stop by my session to learn about Pravega and architecture recommendations for Streaming Analytics.

Information on my session

The proliferation of connected devices and sensors is leading the Digital Transformation. By 2020 there will be over 20 billion connected devices. Data from these devices need to be ingested at extreme speeds in order to be analyzed before the data decays. The life cycle of the data is critical in revealing what insight can be revealed and how quickly they can be acted upon.

In this session we will look at the past, present and future architecture trends of streaming analytics. Next we will look at how to turn all the data from these devices into actionable insights. We will also dive into recommendations for streaming architecture depending on the data streams and time factor of the data. Finally, we will discuss how to manage all the sensor data, understand the life cycle cost of the data, and how to scale capacity and capability easily with a modern infrastructure strategy.